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- Mechanical properties (2)
- Artificial neural network (1)
- Clustering (1)
- Computer vision (1)
- Deep learning (1)
- Dual phase steel (1)
- Eindringprüfung (1)
- High strength steels (1)
- Hochfester Stahl (1)
- Instumented indentation test (1)
Organisationseinheit der BAM
This paper demonstrates that the instrumented indentation test (IIT), together with a trained artificial neural network (ANN), has the capability to characterize the mechanical properties of the local parts of a welded steel structure such as a weld nugget or heat affected zone.
Aside from force-indentation depth curves generated from the IIT, the profile of the indented surface deformed after the indentation test also has a strong correlation with the materials’ plastic behavior. The profile of the indented surface was used as the training dataset to design an ANN to determine the material parameters of the welded zones. The deformation of the indented surface in three dimensions shown in images were analyzed with the computer vision algorithms and the obtained data were employed to train the ANN for the characterization of the mechanical properties. Moreover, this method was applied to the images taken with a simple light microscope from the surface of a specimen. Therefore, it is possible to quantify the mechanical properties of the automotive steels with the four independent methods: (1) force-indentation depth curve; (2) profile of the indented surface; (3) analyzing of the 3D-measurement image; and (4) evaluation of the images taken by a simple light microscope. The results show that there is a very good Agreement between the material parameters obtained from the trained ANN and the experimental uniaxial tensile test. The results present that the mechanical properties of an unknown steel can be determined by only analyzing the images taken from its surface after pushing a simple indenter into its surface.
The determination of mechanical properties of welded Steel structures such as strength or ductility is a subject of high interest for the majority of Companies in the area of metal Processing. The material Parameters can be obtained by performing the tensile test on the samples made from a part of a component. In some cases, it is highly expensive to produce the tensile specimens especially from the weld metal, which contains different type of microstructure such as weld seam or heat affected zone in an extremely small area. Therefore, a method is described in this paper to determine the material Parameters of high strength Steel structures and welded joints locally and without any additional effort to perform the tensile test. In this method, instrumented indentation technique (IIT), an indenter is pushed on the flat surface of a specimen in a certain period of time and simultaneously the applied force and the corresponding indentation path are measured. The data related to the force-indentation diagram is given as input to an artificial neural network (ANN) to obtain the material Parameters. The ANN can be trained by generating the large qualitative data sets with numerical Simulation of the IIT procedure. The Simulation must be run several times with the different material model parameter sets to generate the numerous
force-indentation diagrams as the inputs of ANN. Then, the trained ANN is validated by performing the IIT on the welded joints and comparing the obtained material Parameters from ANN with the tensile test.
Consequently, the mechanical properties of welded joints can be determined by performing the IIT and evaluating the resulting data by the ANN.
Resistance spot welding (RSW) is widely used in the automotive industry
as the main joining method. Generally, an automotive body contains
around 2000 to 5000 spot welds. Therefore, it is of decisive importance to characterize the mechanical properties of these areas for the further optimization and improvement of an automotive body structure. The present paper aims to introduce a novel method to investigate the mechanical properties and microstructure of the resistance spot weldment of DP1000 sheet steel. In this method, the microstructure of RSW of two sheets was reproduced on one sheet and on a bigger area by changing of the welding parameters, e. g. welding current, welding time, electrode force and type. Then, tensile tests in combination with digital Image correlation (DIC) measurement were performed on the notched tensile specimens to determine the mechanical properties of the weld metal.
The notch must be made on the welded tensile specimen to force the fracture and elongation on the weld metal, enabling the characterization of its properties. Additionally, the parameters of a nonlinear isotropic material model can be obtained and verified by the simulation of the tensile specimens. The parameters obtained show that the strength of DP1000 steel and the velocity of dislocations for reaching the Maximum value of strain hardening, are significantly increased after RSW. The effect of sample geometry and microstructural inhomogeneity of the welded joint on the constitutive property of the weld metal are presented and discussed.
Among the various welding technologies, resistance spot welding (RSW) and laser beam welding (LBW) play a significant role as joining methods for the automobile industry. The application of RSW and LBW for the automotive body alters the microstructure in the welded areas. It is necessary to identify the mechanical properties of the welded material to be able to make a reliable statement about the material behavior and the strength of welded components. This study develops a method by which to determine the mechanical properties for the weldment of RSW and LBW for two dual phase (DP) steels, DP600 and DP1000, which are commonly used for the automotive bodies. The mechanical properties of the resistance spot weldment were obtained by performing tensile tests on the notched tensile specimen to cause an elongation of the notched and welded area in order to investigate its properties. In order to determine the mechanical properties of the laser beam weldment, indentation tests were performed on the welded material to calculate its force-penetration depth-curve. Inverse numerical simulation was used to simulate the indentation tests to determine and verify the parameters of a nonlinear isotropic material model for the weldment of LBW. Furthermore, using this method, the parameters for the material model of RSW were verified. The material parameters and microstructure of the weldment of RSW and LBW are compared and discussed. The results show that the novel method introduced in this work is a valid approach to determine the mechanical properties of welded high-strength steel structures. In addition, it can be seen that LBW and RSW lead to a reduction in ductility and an increase in the amount of yield and tensile strength of both DP600 and DP1000.
Der Einsatz von hochfesten Stählen im Karosseriebereich des Automobilbaus hat während der letzten Jahre stark zugenommen. Hierzu zählen Dual- und Komplexphasenstähle, welche durch Kombination unterschiedlicher Gefügebestandteile auch deren Vorteile kombinieren, sowie TRIP (TRansformation Induced Plasticity) und Mangan-Bor Stähle, welche sehr gute Umformeigenschaften mit hohen Festigkeiten durch Martensitbildung bei der Umformung kombinieren. TWIP (Twinning Induced Plasticity) Stähle erreichen ähnliche Effekte durch forcierte Zwillingsbildung.
Die Ursachen für den Einsatz dieser Stähle liegen in dem Potential dieser Materialien zur Gewichts- und Kostenreduzierung, bei gleichzeitiger Erhöhung der Fahrgastsicherheit. Auf Grund der prinzipiell gegebenen Schweißeignung dieser Stähle, werden die klassischen Fügeverfahren im Karosseriebau wie das kostengünstige und effektive Widerstandspunktschweißen, das Metall-Schutzgas (MSG)-Schweißen oder das Laserschweißen angewendet. Allerdings treten teilweise Herausforderungen, beispielsweise durch Gefügeveränderungen in den Fügestellen auf, die zu ungewollten Aufhärtungen oder Erweichungen führen.
In diesem Projekt wird ein Verfahren entwickelt, mit welchem die lokalen Werkstoffeigenschaften von im Automobilbau typischen Werkstoffen und deren Fügestellen bestimmt werden können. Relevante Kennwerte sind in erster Linie das SpannungsDehnungs-Verhalten der verschiedenen Zonen einer Schweißverbindung; relevante Zonen wiederum sind neben dem Grundwerkstoff die Wärmeeinflusszone und das Schweißgut. Zu diesem Zweck wird das Verfahren der instrumentierten Eindringprüfung für den Einsatz bei hochfesten Stählen weiterentwickelt. Zunächst werden hierzu Zugversuche an einfachen Grundwerkstoffgeometrien durchgeführt. Im Anschluss wird die optische Dehnungsfeldmessung an stark taillierten, geschweißten Zugversuchsproben durchgeführt.
Die Taillierung dient dem Zweck, die WEZ auch mittels WPS über den gesamten Querschnitt der Probe erzeugen zu können, bzw. im Versuch auch Dehnungen in den relevanten Bereichen herbeizuführen.
Das im Projekt angewendete Auswerteverfahren, welches auf nichtlinearen Regressionsmodellen in Form von künstlichen, neuronalen Netzwerken beruht, ermöglicht die Vorhersage des Festigkeitsverhaltens des Werkstoffes anhand der gemessenen Krafteindringwegdaten.